Instructions to use Muapi/multiple-insertion-penetration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/multiple-insertion-penetration with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cocktailpeanut/pony-diffusion-v6-xl", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/multiple-insertion-penetration") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- d65c418f46663af0c3fe9073cf7526593d668bdb548a07856076524597c1a877
- Size of remote file:
- 57.5 MB
- SHA256:
- b8d50d1f6985d10582a13235b837be2be09850e469e433710d037bdc7a578369
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